Abnormality diagnosis method, abnormality diagnosis apparatus, non-transitory computer-readable medium storing abnormality diagnosis program, and abnormality diagnosis system

An abnormality diagnosis apparatus to diagnose whether there is abnormality in a facility to be diagnosed, the abnormality diagnosis apparatus comprising:

• a data reader to obtain from the facility, data having a quantity of state of a single assessment item or a plurality of assessment items;
• a data classifier to classify for each operation state of the facility, the data obtained from the facility;
• a parameter calculator and holder to assess sufficiency of the number of pieces of data for each classified data group, to calculate a plurality of parameter values configuring a trained model in accordance with the sufficiency of the number of pieces of data, and to hold the parameter values in association with the operation state;
• a parameter obtaining unit to obtain the plurality of parameter values configuring the trained model without overlaps for each parameter, in accordance with the operation state of the data to be diagnosed and a status of holding of the parameter values associated with each operation state;
• a trained model creator to create a trained model to diagnose the data to be diagnosed, with the obtained parameter values;
• an abnormality degree calculator to calculate a degree of abnormality for determination as to abnormality based on the trained model;
• and p1 an abnormality determination unit to determine, based on the degree of abnormality, whether there is abnormality in a diagnosis target, wherein:
• the parameter obtaining unit obtains all parameter values configuring the trained model based on a fact that the all parameter values are held in an operation state identical to the operation state of data to be diagnosed;
• and
• the parameter obtaining unit obtains, based on a fact that only some of parameter values configuring the trained model is held in the operation state identical to the operation state of the data to be diagnosed, only some of the parameter values and obtaining remaining parameter values from parameter values of an identical type held in another operation state.

A non-transitory computer-readable medium storing abnormality diagnosis program to cause a computer to perform processing for diagnosing whether there is abnormality in a facility to be diagnosed, the abnormality diagnosis program causing the computer to perform:

• obtaining from the facility, data having a quantity of state of a single assessment item or a plurality of assessment items;
• classifying for each operation state of the facility, the data obtained from the facility;
• assessing sufficiency of the number of pieces of data for each classified data group;
• calculating a plurality of parameter values configuring a trained model in accordance with the sufficiency of the number of pieces of data and holding the parameter values in association with the operation state;
• obtaining the plurality of parameter values configuring the trained model without overlaps for each parameter, in accordance with the operation state of the data to be diagnosed and a status of holding of the parameter values associated with each operation state;
• creating a trained model to diagnose the data to be diagnosed, with the obtained parameter values;
• calculating a degree of abnormality for determination as to abnormality based on the trained model;
• and p1 determining whether there is abnormality in a diagnosis target based on the degree of abnormality, p1 wherein the obtaining the plurality of parameter values configuring the trained model without overlaps for each parameter, in accordance with the operation state of the data to be diagnosed and a status of holding of the parameter values associated with each operation state comprises:
• obtaining all parameter values configuring the trained model based on a fact that the all parameter values are held in an operation state identical to the operation state of data to be diagnosed;
• and
• obtaining, based on a fact that only some of parameter values configuring the trained model is held in the operation state identical to the operation state of the data to be diagnosed, only some of the parameter values and obtaining remaining parameter values from parameter values of an identical type held in another operation state.

An abnormality diagnosis system to diagnose whether there is abnormality in a facility to be diagnosed, comprising:

• a data reader to obtain from the facility, data having a quantity of state of a single assessment item or a plurality of assessment items;
• a data classifier to classify for each operation state of the facility, the data obtained from the facility;
• a parameter calculator and holder to assess sufficiency of the number of pieces of data for each classified data group, to calculate a plurality of parameter values configuring a trained model in accordance with the sufficiency of the number of pieces of data, and to hold the parameter values in association with the operation state;
• a parameter obtaining unit to obtain the plurality of parameter values configuring the trained model without overlaps for each parameter, in accordance with the operation state of the data to be diagnosed and a status of holding of the parameter values associated with each operation state;
• a trained model creator to create a trained model to diagnose the data to be diagnosed, with the obtained parameter values;
• an abnormality degree calculator to calculate a degree of abnormality for determination as to abnormality based on the trained model;
• and p1 an abnormality determination unit to determine whether there is abnormality in a diagnosis target based on the degree of abnormality, p1 wherein the obtaining the plurality of parameter values configuring the trained model without overlaps for each parameter, in accordance with the operation state of the data to be diagnosed and a status of holding of the parameter values associated with each operation state comprises:
• obtaining all parameter values configuring the trained model based on a fact that the all parameter values are held in an operation state identical to the operation state of data to be diagnosed;
• and
• obtaining, based on a fact that only some of parameter values configuring the trained model is held in the operation state identical to the operation state of the data to be diagnosed, only some of the parameter values and obtaining remaining parameter values from parameter values of an identical type held in another operation state.